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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Plutonium Oxidation State Distribution under WIPP Relevant Conditions (Rev. 2)

The oxidation state of plutonium in the Waste Isolation Pilot Plant (WIPP) environment has been a topic of interest since the initial compliance certification application. Plutonium (Pu) was initially expected to be present primarily as Pu(IV), but since the presence of Pu(III) could not be ruled out, it was also included in performance assessment (PA) calculations. The redox of the other variant actinides, uranium (U) and neptunium (Np), are also coupled to the plutonium redox. This led to a position in performance assessment calculations that is commonly referred to as “50/50”. In which half of the PA realizations assume solubility is dominated by the low oxidation state [U(IV), Np(IV), Pu(III)] and the other half assume solubility is dominated by the higher oxidation state [U(VI), Np(V), Pu(IV)]. Recently, a joint group of WIPP project participants from Los Alamos National Laboratory (LANL), Sandia National Laboratories (SNL), and the Department of Energy’s Carlsbad Field Office (DOE-CBFO) agreed on a new path forward for the oxidation state model in PA which will decouple the redox active actinides and will instead consider their redox as a function of E h . This will take the current binary approach and turn it into a system with four possible redox states.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Second Report of the Nuclear Data Subcommittee of the Nuclear Science Advisory Committee

The central importance of the nuclear data curated by the US Nuclear Data Program (USNDP) for clean energy generation, national security, nonproliferation, medical applications, and space exploration as well as basic science was described in a prior report issued by the DOE/NSF Nuclear Science Advisory Committee subcommittee on Nuclear Data (NSAC-ND) in September 2022. In this report, we present a set of fourteen (14) recommendations that will enhance and advance DOE-NP's stewardship of nuclear data. The first three recommendations focus on the existing core USNDP capabilities, namely: 1) Support the nuclear structure evaluation workforce to improve the currency, consistency, and accessibility of the Evaluated Nuclear Structure Data File (ENSDF); 2) Enhance nuclear reaction evaluation within the USNDP in support of the Evaluated Nuclear Data File (ENDF) through expansion of the workforce and integration of high-performance computing, automation, and machine learning and; 3) Continue atomic mass evaluation in support AME and NUBASE databases. This is followed by eight (8) recommendations representing new cross-cutting initiatives involving both measurement and evaluation to address outstanding nuclear data needs. These new initiatives require a highly trained, diverse workforce that includes personnel with expertise from both inside and outside the nuclear physics community from which evaluators have traditionally been recruited. As such, many of these initiatives are accomplished via a Topical Nuclear Data Collaborations (TNDC). A TNDC is made up of domestic and international stakeholders, subject matter and nuclear data experts, and nuclear data evaluators and features a workforce development plan to ensure that nuclear data evaluators maintain currency in the relevant applications and are seen as equity partners in the endeavor. These include: 1) Establish a coordinated effort to improve evaluation and modeling in nuclear astrophysics for stellar dynamics, multi-messenger astronomy and nucleosynthesis; 2) Initiate a TNDC to develop and maintain nuclear structure evaluation beyond discrete states, including nuclear level densities, photon strength functions and photonuclear data for improved reaction modeling, and exploring nuclear structure at finite temperature; 3) Create a TNDC to perform correlated fission data evaluation, including cross sections, fragment yields, v(A), v(E n ) for nuclear energy, national security, nonproliferation and basic science; 4) From a panel of subject matter experts to establish and annually update a roster of key decay data to nurture its accelerated dissemination including both measurement and evaluation for targeted high-value nuclides for national security, nonproliferation and medical applications; 5) Comprehensive, consistent neutron-induced structure and reaction data for nuclear energy, national security, nonproliferation and planetary nuclear spectroscopy; 6) Charged-particle stopping powers for detector design, space effects and ion beam therapy; 7) High-energy reactions for space exploration and medical nuclide production, and; 8) The creation of an infrastructure for open data and data preservation for use by the entire nuclear physics community. All told, these initiatives require approximately $6.5M increase in NP support of the USNDP in fiscal year 2023 dollars and would require at least 3-5 years to carry out due to the length of time needed to recruit and train new nuclear data researchers. This relatively modest investment would help ensure that the fruits of the nuclear data research carried out by DOE-NP and its collaborators would be brought to bear to address some of the most important needs of our nation and the world. To ensure effective execution of this plan, we present an overview of recruitment, training, and retention goals for the USNDP, the centerpiece of which is a mutually agreed upon code of conduct. Finally, we identify the facility and instrumentation needed to perform the recommended experimental activities. This includes a short review of target fabrication capabilities, reactors, neutron beam, light- and heavy-stable ion, gamma-ray, high-energy and radioactive ion beam facilities. Lastly, a more complete appendix of experimental facilities previously compiled is included with new input provided for 6 facilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Nuclear Physics Network Requirements Review (Final Report)

The Energy Sciences Network (ESnet) is the high-performance network user facility for the US Department of Energy (DOE) Office of Science (SC) and delivers highly reliable data transport capabilities optimized for the requirements of data-intensive science. In essence, ESnet is the circulatory system that enables the DOE science mission by connecting all its laboratories and facilities in the US and abroad. ESnet is funded and stewarded by the Advanced Scientific Computing Research (ASCR) program and managed and operated by the Scientific Networking Division at Lawrence Berkeley National Laboratory (LBNL). ESnet is widely regarded as a global leader in the research and education networking community. ESnet interconnects DOE national laboratories, user facilities, and major experiments so that scientists can use remote instruments and computing resources as well as share data with collaborators, transfer large datasets, and access distributed data repositories. ESnet is specifically built to provide Between July 2023 and October 2023, ESnet and the Nuclear Physics program (NP) of the DOE SC organized an ESnet requirements review of NP-supported activities. Preparation for these events included identification of key stakeholders: program and facility management, research groups, and technology providers. Each stakeholder group was asked to prepare formal case study documents about its relationship to the NP program to build a complete understanding of the current, near-term, and long-term status, expectations, and processes that will support the science going forward.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

V-INT: Automated Vulnerability Intelligence and Risk Assessment

The project team, including the University of Arkansas (UA) as the lead, the University of Arkansas at Little Rock (UALR), Network Perception (NP), and Bastazo, has successfully researched, developed, and demonstrated the V-INT toolset, and also integrated it into the commercial products of NP (i.e., NP-View) and Bastazo (i.e., Spartan). The end product is a cybersecurity software tool for energy utilities that can automatically assess the risks of software vulnerabilities in an organization’s assets considering the organization’s firewall policies. It allows security operators to identify the small portion of vulnerabilities that poses true threats to their system (i.e., those that are not protected by firewall policies) and prioritize the mitigation of these vulnerabilities to minimize risks. It also allows security operators to identify the vulnerability-induced attack paths under their organization’s firewall policy, providing effective decision supports for mitigating potential attacks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Neptunium mononitride as a target material for Pu-238 production

Deep space exploration requires specialized sources for both thermal and power applications. Radioactive decay heat of plutonium-238 (238Pu) provides these sources in the form of radioisotope thermoelectric generators (RTGs). The 238 Pu is produced via neutron capture reaction involving neptunium-237 ( 237 Np) target material. Continual optimization of 237 Np target materials and evaluation of potential alternative targets for production of 238 Pu RTGs are advantageous for meeting ongoing space power system resource requirements. Current production of 238 Pu for RTGs for the United States space program utilizes neptunium dioxide ( 237 NpO 2 ) targets; however, the use of neptunium mononitride ( 237 NpN) presents an opportunity to increase the mass of 237 Np per target compared to the dioxide form, as well as increase the thermal conductivity of the target. To assess the viability of a 237 NpN target material, the material chemistry must be thoroughly evaluated, including synthesis methods and dissolution and reprocessing schemes. This review presents a summary of synthesis pathways for 237 NpN based on published literature on actinide mononitrides. Specific literature on 237 NpN is limited, necessitating evaluation of other actinide systems to gather parallels. This suggests a need for additional experimental studies on 237 NpN. A particular limitation in the existing literature is a lack of information on the differences in material characteristics, such as morphology, particle size, and trace chemical impurities, as a function of synthesis method. These parameters may affect subsequent reactor performance or dissolution of irradiated targets. The evaluation of existing literature is presented with a focus on the efficacy of 237 NpN targets for 238 Pu production.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

Sustainable Valorization of CO2 through Nuclear Power-to-X Pathways

Some of the issues concerning energy security and climate change can be addressed by employing nuclear power (NP) to supply the energy required for the conversion of carbon dioxide (CO2) into chemicals, products, and materials. Nuclear energy represents a neutral carbon source that can be generated sustainably, reliably, and consistently. Nuclear power plants (NPPs) could supply energy in the form of heat, electricity, and ionizing radiation to drive CO2 chemical reactions underpinning NP-to-X type of pathways. CO2 conversion processes are either commercially available or emerging technologies at different developmental maturity stages. This work reviews the published literature (articles and patents) that reports R&D results and the understanding and development of chemical reactions and processes, as well as the efforts in integrating NPPs and chemical processes (CPs). As will be made evident, a new industrial era for the manufacturing of decarbonized chemicals, products, and materials will be possible by developing and implementing new (more energy- and carbon-efficient) processes responding to the NP-to-X pathways. This new decarbonizing platform not only contributes to achieving net zero goals but also broadens the NPP product beyond electricity.

08 HYDROGEN↗
NASA NTRS1978

Oscillator strength trends in group IVb homologous ions

Shock tube data are used to examine the systematic f value behavior in prominent visible transition arrays (ns-np, np-(n+l)s, np-nd) for the homologous emitter sequence Si 11, Ge 11, Sn 11, and Pb 11. Regularities found for these data are compared with trends in lighter elements. Agreements and s disparities with theoretical and experimental oscillator strengths from the literature are noted.

Miller, M. H.↗
NASA NTRS1989

Minimizing distortion and internal forces in truss structures by simulated annealing

Inaccuracies in the length of members and the diameters of joints of large truss reflector backup structures may produce unacceptable levels of surface distortion and member forces. However, if the member lengths and joint diameters can be measured accurately it is possible to configure the members and joints so that root-mean-square (rms) surface error and/or rms member forces is minimized. Following Greene and Haftka (1989) it is assumed that the force vector f is linearly proportional to the member length errors e(sub M) of dimension NMEMB (the number of members) and joint errors e(sub J) of dimension NJOINT (the number of joints), and that the best-fit displacement vector d is a linear function of f. Let NNODES denote the number of positions on the surface of the truss where error influences are measured. The solution of the problem is discussed. To classify, this problem was compared to a similar combinatorial optimization problem. In particular, when only the member length errors are considered, minimizing d(sup 2)(sub rms) is equivalent to the quadratic assignment problem. The quadratic assignment problem is a well known NP-complete problem in operations research literature. Hence minimizing d(sup 2)(sub rms) is is also an NP-complete problem. The focus of the research is the development of a simulated annealing algorithm to reduce d(sup 2)(sub rms). The plausibility of this technique is its recent success on a variety of NP-complete combinatorial optimization problems including the quadratic assignment problem. A physical analogy for simulated annealing is the way liquids freeze and crystallize. All computational experiments were done on a MicroVAX. The two interchange heuristic is very fast but produces widely varying results. The two and three interchange heuristic provides less variability in the final objective function values but runs much more slowly. Simulated annealing produced the best objective function values for every starting configuration and was faster than the two and three interchange heuristic.

Kincaid, Rex K.↗
NASA NTRS1990

Matrix effects for reflectivity spectra of dispersed nanophase (superparamagnetic) hematite with application to Martian spectral data

The effect of the matrix on the reflectivity spectra of nanophase (superparamagnetic) hematite (np-Hm) dispersed within the matrix was investigated in four series of powder samples containing np-Hm dispersed within discrete powder particles (of two size ranges) of silica gel and activated alumina. The spectral data show that matrix effects are large. Samples with the same Fe2O3 content can have np-Hm absorption edges characterized by very different positions and curvature and slope indices, while samples with equivalent absorption edges can have very different Fe2O3 concentrations. Thus, quantitative relationships between the positions of ferric absorption edges and Fe2O3 concentrations are unreliable without knowledge of matrix properties of the system. It is shown that it was possible to match the Fe2O3 concentration, magnetic properties, and spectral data for Martian surface material with a laboratory mixture whose only ferric-bearing phase was hematite.

Morris, Richard V.↗
NASA NTRS2005

Statistical Considerations of Data Processing in Giovanni Online Tool

The GES DISC Interactive Online Visualization and Analysis Infrastructure (Giovanni) is a web-based interface for the rapid visualization and analysis of gridded data from a number of remote sensing instruments. The GES DISC currently employs several Giovanni instances to analyze various products, such as Ocean-Giovanni for ocean products from SeaWiFS and MODIS-Aqua; TOMS & OM1 Giovanni for atmospheric chemical trace gases from TOMS and OMI, and MOVAS for aerosols from MODIS, etc. (http://giovanni.gsfc.nasa.gov) Foremost among the Giovanni statistical functions is data averaging. Two aspects of this function are addressed here. The first deals with the accuracy of averaging gridded mapped products vs. averaging from the ungridded Level 2 data. Some mapped products contain mean values only; others contain additional statistics, such as number of pixels (NP) for each grid, standard deviation, etc. Since NP varies spatially and temporally, averaging with or without weighting by NP will be different. In this paper, we address differences of various weighting algorithms for some datasets utilized in Giovanni. The second aspect is related to different averaging methods affecting data quality and interpretation for data with non-normal distribution. The present study demonstrates results of different spatial averaging methods using gridded SeaWiFS Level 3 mapped monthly chlorophyll a data. Spatial averages were calculated using three different methods: arithmetic mean (AVG), geometric mean (GEO), and maximum likelihood estimator (MLE). Biogeochemical data, such as chlorophyll a, are usually considered to have a log-normal distribution. The study determined that differences between methods tend to increase with increasing size of a selected coastal area, with no significant differences in most open oceans. The GEO method consistently produces values lower than AVG and MLE. The AVG method produces values larger than MLE in some cases, but smaller in other cases. Further studies indicated that significant differences between AVG and MLE methods occurred in coastal areas where data have large spatial variations and a log-bimodal distribution instead of log-normal distribution.

Suhung, Shen↗
NASA NTRS2014

F Ring Core Stability: Corotation Resonance Plus Antiresonance

The decades-or-longer stability of the narrow F Ring core in a sea of orbital chaos appears to be due to an unusual combination of traditional corotation resonance and a novel kind of "antiresonance". At a series of specific locations in the F Ring region, apse precession between synodic encounters with Prometheus allows semimajor axis perturbations to promptly cancel before significant orbital period changes can occur. This cancellation fails for particles that encounter Prometheus when it is near its apoapse, especially during periods of antialignment of its apse with that of the F Ring. At these times, the strength of the semimajor axis perturbation is large (tens of km) and highly nonsinusoidal in encounter longitude, making it impossible to cancel promptly on a subsequent encounter and leading to chaotic orbital diffusion. Only particles that consistently encounter Prometheus away from its apoapse can use antiresonance to maintain stable orbits, implying that the true mean motion nF of the stable core must be defined by a corotational resonance of the form nF = nP(-kappa)P/m, where (nP, kappaP) are Prometheus' mean motion and epicycle frequency. To test this hypothesis we used the fact that Cassini RSS occultations only sporadically detect a "massive" F Ring core, composed of several-cm-and-larger particles. We regressed the inertial longitudes of 24 Cassini RSS (and VGR) detections and 43 nondetections to a common epoch, using a comb of candidate nP, and then folded them modulo the anticipated m-number of the corotational resonance (Prometheus m = 110 outer CER), to see if clustering appears. We find the "true F Ring core" is actually arranged in a series of short longitudinal arcs separated by nearly empty longitudes, orbiting at a well determined semimajor axis of 140222.4 km (from 2005-2012 at least). Small particles seen by imaging and stellar occultations spread quickly in azimuth and obscure this clumpy structure. Small chaotic variations in the mean motion and/or apse longitude of Prometheus quickly become manifest in the F Ring core, and we suggest that the core must adapt to these changes for the F Ring to maintain stability over timescales of decades and longer

Cassini RSS occultations↗
DOE OSTI2020

Nuclear reactor assemblies, nuclear reactor target assemblies, and nuclear reactor methods

Reactor target assemblies are provided that can include a housing defining a perimeter of at least one volume and Np or Am spheres within the one volume. Reactor assemblies are provided that can include a reactor vessel and a bundle of target assemblies within the reactor vessel, at least one of the target assemblies comprising a housing defining a volume with Np or Am spheres being within the volume. Irradiation methods are also provided that can include irradiating Np or Am spheres within a nuclear reactor, then removing the irradiated spheres from the reactor and treating the irradiated spheres.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Extending Power of Nature from Binary Problems to Real-Valued Graph Learning in Real World

Nature performs complex computations constantly at clearly lower cost and higher performance than digital computers. It is crucial to understand how to harness the unique computational power of nature in Machine Learning (ML). In the past decade, besides the development of Neural Networks (NNs), the community has also relentlessly explored nature-powered ML paradigms. Although most of them are still predominantly theoretical, a new practical paradigm enabled by the recent advent of CMOS-compatible room-temperature nature-based computers has emerged. By harnessing the nature's power of entropy increase, this paradigm can solve binary learning problems delivering immense speedup and energy savings compared with NNs, while maintaining comparable accuracy. Regrettably, its values to the real world are highly constrained by its binary nature. A clear pathway to its extension to real-valued problems remains elusive. This paper aims to unleash this pathway by proposing a novel end-to-end Nature-Powered Graph Learning (NP-GL) framework. Specifically, through a three-dimensional co-design, NP-GL can leverage the nature's power of entropy increase to efficiently solve real-valued graph learning problems. Experimental results across 4 real-world applications with 6 datasets demonstrate that NP-GL delivers, on average, 6970X speedup and 10^5x energy consumption reduction with comparable or even higher accuracy than Graph Neural Networks (GNNs).

artificial intelligence↗
DOE OSTI2025

Charged Lepton Flavour Violations searches with muons: present and future

Charged-lepton flavor violation (cLFV) is one of the most powerful probes for New Physics (NP). Since lepton flavor conservation is an accidental symmetry in the Standard Model (SM), it is naturally violated in many NP models, with contributions at the level of the current experimental sensitivities. Moreover, the negligible SM contributions would make the observation of cLFV unambiguous evidence of NP. It makes these searches extremely sensitive and, at the same time, extremely pure. Thanks to the intense muon beams currently available, their intriguing upgrade programs, and the progress in the detection techniques, cLFV muon processes are the golden channels in this field. Experimental programs to search for $\mu^+ \to e^+ \gamma$, $\mu^+ \to e^+ e^+ e^-$ and the $\mu \to e$ conversion in the nuclear field are currently ongoing. We review the current status and the strategic plans for future searches. This document is an update of the prior cLFV submission to the 2018 European Strategy for Particle Physics (ESPP); the earlier submission should be consulted for more experimental details.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

A Data Deposition Platform for Sharing Nuclear Magnetic Resonance Data

Nuclear magnetic resonance (NMR) data are rarely deposited in open databases, leading to loss of critical scientific knowledge. Existing data reporting methods (images, tables, lists of values) contain less information than raw data, and are poorly standardized. Together, these issues limit FAIR (findable, accessible, interoperable, reusable) access to these data, which in turn creates barriers for compound dereplication and the development of new data-driven discovery tools. Existing NMR databases are either not designed for natural products data, or employ complex deposition interfaces that disincentivize deposition. Journals, including the Journal of Natural Products (JNP), are now requiring data submission as part of the publication process, creating the need for a streamlined, user-friendly mechanism to deposit and distribute NMR data. Recently, our team reported the development of the Natural Products Magnetic Resonance Database (NP-MRD; www.np-mrd.org). Here in this paper we present a new data deposition platform for the NP-MRD project that is designed to enable users to deposit NMR data for published or submitted manuscripts in under five minutes. This platform includes a suite of automated data extraction and standardization tools, together with a simple-to-use web-based interface and detailed error reporting to simplify the data deposition process and is available at www.np-mrd.org/submissions.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2020

Materials Data on NpAsS by Materials Project

NpAsS is Matlockite structured and crystallizes in the tetragonal P4/nmm space group. The structure is three-dimensional. Np5+ is bonded in a 5-coordinate geometry to four equivalent As3- and five equivalent S2- atoms. All Np–As bond lengths are 3.07 Å. There are four shorter (2.79 Å) and one longer (2.80 Å) Np–S bond lengths. As3- is bonded to four equivalent Np5+ and four equivalent As3- atoms to form distorted AsNp4As4 hexagonal bipyramids that share corners with four equivalent AsNp4As4 hexagonal bipyramids, corners with twelve equivalent SNp5 square pyramids, edges with four equivalent AsNp4As4 hexagonal bipyramids, edges with four equivalent SNp5 square pyramids, and faces with four equivalent AsNp4As4 hexagonal bipyramids. All As–As bond lengths are 2.73 Å. S2- is bonded to five equivalent Np5+ atoms to form distorted SNp5 square pyramids that share corners with twelve equivalent AsNp4As4 hexagonal bipyramids, corners with four equivalent SNp5 square pyramids, edges with four equivalent AsNp4As4 hexagonal bipyramids, and edges with eight equivalent SNp5 square pyramids.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on NpPO4F by Materials Project

NpPO4F crystallizes in the orthorhombic Pnma space group. The structure is three-dimensional. Np4+ is bonded in a 6-coordinate geometry to six O2- and two equivalent F1- atoms. There are a spread of Np–O bond distances ranging from 2.23–2.65 Å. Both Np–F bond lengths are 2.29 Å. P5+ is bonded in a tetrahedral geometry to four O2- atoms. There is two shorter (1.53 Å) and two longer (1.57 Å) P–O bond length. There are three inequivalent O2- sites. In the first O2- site, O2- is bonded in a distorted bent 150 degrees geometry to one Np4+ and one P5+ atom. In the second O2- site, O2- is bonded in a 2-coordinate geometry to two equivalent Np4+ and one P5+ atom. In the third O2- site, O2- is bonded in a distorted bent 150 degrees geometry to one Np4+ and one P5+ atom. F1- is bonded in a distorted bent 150 degrees geometry to two equivalent Np4+ atoms.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on NpSi by Materials Project

NpSi crystallizes in the orthorhombic Cmcm space group. The structure is three-dimensional. there are two inequivalent Np4+ sites. In the first Np4+ site, Np4+ is bonded to six equivalent Si4- atoms to form distorted edge-sharing NpSi6 pentagonal pyramids. There are two shorter (2.90 Å) and four longer (2.93 Å) Np–Si bond lengths. In the second Np4+ site, Np4+ is bonded in a 8-coordinate geometry to eight equivalent Si4- atoms. There are four shorter (2.95 Å) and four longer (3.07 Å) Np–Si bond lengths. Si4- is bonded in a 9-coordinate geometry to seven Np4+ and two equivalent Si4- atoms. There are one shorter (2.43 Å) and one longer (2.45 Å) Si–Si bond lengths.

36 MATERIALS SCIENCE↗